A single-center, retrospective study of hospitalized patients with lower respiratory tract infections: clinical assessment of metagenomic next-generation sequencing and identification of risk factors in patients.

INTRODUCTION: Lower respiratory tract infections(LRTIs) in adults are complicated by diverse pathogens that challenge traditional detection methods, which are often slow and insensitive. Metagenomic next-generation sequencing (mNGS) offers a comprehensive, high-throughput, and unbiased approach to pathogen identification. This retrospective study evaluates the diagnostic efficacy of mNGS compared to conventional microbiological testing (CMT) in LRTIs, aiming to enhance detection accuracy and enable early clinical prediction. METHODS: In our retrospective single-center analysis, 451 patients with suspected LRTIs underwent mNGS testing from July 2020 to July 2023. We assessed the pathogen spectrum and compared the diagnostic efficacy of mNGS to CMT, with clinical comprehensive diagnosis serving as the reference standard. The study analyzed mNGS performance in lung tissue biopsies and bronchoalveolar lavage fluid (BALF) from cases suspected of lung infection. Patients were stratified into two groups based on clinical outcomes (improvement or mortality), and we compared clinical data and conventional laboratory indices between groups. A predictive model and nomogram for the prognosis of LRTIs were constructed using univariate followed by multivariate logistic regression, with model predictive accuracy evaluated by the area under the ROC curve (AUC). RESULTS: (1) Comparative Analysis of mNGS versus CMT: In a comprehensive analysis of 510 specimens, where 59 cases were concurrently collected from lung tissue biopsies and BALF, the study highlights the diagnostic superiority of mNGS over CMT. Specifically, mNGS demonstrated significantly higher sensitivity and specificity in BALF samples (82.86% vs. 44.42% and 52.00% vs. 21.05%, respectively, p < 0.001) alongside greater positive and negative predictive values (96.71% vs. 79.55% and 15.12% vs. 5.19%, respectively, p < 0.01). Additionally, when comparing simultaneous testing of lung tissue biopsies and BALF, mNGS showed enhanced sensitivity in BALF (84.21% vs. 57.41%), whereas lung tissues offered higher specificity (80.00% vs. 50.00%). (2) Analysis of Infectious Species in Patients from This Study: The study also notes a concerning incidence of lung abscesses and identifies Epstein-Barr virus (EBV), Fusobacterium nucleatum, Mycoplasma pneumoniae, Chlamydia psittaci, and Haemophilus influenzae as the most common pathogens, with Klebsiella pneumoniae emerging as the predominant bacterial culprit. Among herpes viruses, EBV and herpes virus 7 (HHV-7) were most frequently detected, with HHV-7 more prevalent in immunocompromised individuals. (3) Risk Factors for Adverse Prognosis and a Mortality Risk Prediction Model in Patients with LRTIs: We identified key risk factors for poor prognosis in lower respiratory tract infection patients, with significant findings including delayed time to mNGS testing, low lymphocyte percentage, presence of chronic lung disease, multiple comorbidities, false-negative CMT results, and positive herpesvirus affecting patient outcomes. We also developed a nomogram model with good consistency and high accuracy (AUC of 0.825) for predicting mortality risk in these patients, offering a valuable clinical tool for assessing prognosis. CONCLUSION: The study underscores mNGS as a superior tool for lower respiratory tract infection diagnosis, exhibiting higher sensitivity and specificity than traditional methods.

A metagenomic assessment of bacterial community in spices sold open-air markets in Saint-Louis, Senegal.

Natural spices play an essential role in human nutrition and well-being. However, their processing on different scales can expose them to potential sources of contamination. This study aimed to describe the bacterial community genomic footprint in spices sold in Senegal. Spice samples were collected in August 2022 in Saint-Louis, Senegal. The genomic region coding bacterial 16S rRNA was then amplified and sequenced using Oxford Nanopore Technology (ONT). Sequencing was carried out on two batches of samples, one containing part of the "Local Spices or Herbs" (n = 10), and the other, a mixture of 7 spices, Curcuma, Thyme and the other part of the "Local Spices or Herbs" (n = 39). Results showed high bacterial diversity and the predominance of Escherichia coli and Salmonella enterica in samples, with total reads of 65,744 and 165,325 for the two batches, respectively. The sample category "Homemade mixture of food condiments ", which includes all "Local Spices or Herbs" samples, showed remarkable bacterial diversity. These were followed by Curcuma, a blend of 7 spices and thyme. Also, the different categories of spices studied show similarities in their bacterial composition. These results highlight the microbial community's highly diverse genomic profile, including pathogenic bacteria, in spice samples.

A set of nematode rRNA cistron databases and a primer assessment tool to enable more flexible and comprehensive metabarcoding.

The ITS-2-rRNA has been particularly useful for nematode metabarcoding but does not resolve all phylogenetic relationships, and reference sequences are not available for many nematode species. This is a particular issue when metabarcoding complex communities such as wildlife parasites or terrestrial and aquatic free-living nematode communities. We have used markerDB to produce four databases of distinct regions of the rRNA cistron: the 18S rRNA gene, the 28S rRNA gene, the ITS-1 intergenic spacer and the region spanning ITS-1_5.8S_ITS-2. These databases comprise 2645, 254, 13,461 and 10,107 unique full-length sequences representing 1391, 204, 1837 and 1322 nematode species, respectively. The comparative analysis illustrates the complementary value but also reveals a better representation of Clade III, IV and V than Clade I and Clade II nematodes in each case. Although the ITS-1 database includes the largest number of unique full-length sequences, the 18S rRNA database provides the widest taxonomic coverage. We also developed PrimerTC, a tool to assess primer sequence conservation across any reference sequence database, and have applied it to evaluate a large number of previously published rRNA cistron primers. We identified sets of primers that currently provide the broadest taxonomic coverage for each rRNA marker across the nematode phylum. These new resources will facilitate more comprehensive metabarcoding of nematode communities using either short-read or long-read sequencing platforms. Further, PrimerTC is available as a simple WebApp to guide or assess PCR primer design for any genetic marker and/or taxonomic group beyond the nematode phylum.

Assessment of antibiotic resistance genes in soils polluted by chemical and technogenic ways with poly-aromatic hydrocarbons and heavy metals.

Anthropogenic activities are leaving lots of chemical footprints on the soil. It alters the physiochemical characteristics of the soil thereby modifying the natural soil microbiome. The prevalence of antimicrobial-resistance microbes in polluted soil has gained attention due to its obvious public health risks. This study focused on assessing the prevalence and distribution of antibiotic-resistance genes in polluted soil ecosystems impacted by industrial enterprises in southern Russia. Metagenomic analysis was conducted on soil samples collected from polluted sites using various approaches, and the prevalence of antibiotic-resistance genes was investigated. The results revealed that efflux-encoding pump sequences were the most widely represented group of genes, while genes whose products replaced antibiotic targets were less represented. The level of soil contamination increased, and there was an increase in the total number of antibiotic-resistance genes in proteobacteria, but a decrease in actinobacteria. The study proposed an optimal mechanism for processing metagenomic data in polluted soil ecosystems, which involves mapping raw reads by the KMA method, followed by a detailed study of specific genes. The study's conclusions provide valuable insights into the prevalence and distribution of antibiotic-resistance genes in polluted soils and have been illustrated in heat maps.

High-throughput DNA extraction and cost-effective miniaturized metagenome and amplicon library preparation of soil samples for DNA sequencing.

Reductions in sequencing costs have enabled widespread use of shotgun metagenomics and amplicon sequencing, which have drastically improved our understanding of the microbial world. However, large sequencing projects are now hampered by the cost of library preparation and low sample throughput, comparatively to the actual sequencing costs. Here, we benchmarked three high-throughput DNA extraction methods: ZymoBIOMICS™ 96 MagBead DNA Kit, MP BiomedicalsTM FastDNATM-96 Soil Microbe DNA Kit, and DNeasy® 96 PowerSoil® Pro QIAcube® HT Kit. The DNA extractions were evaluated based on length, quality, quantity, and the observed microbial community across five diverse soil types. DNA extraction of all soil types was successful for all kits, however DNeasy® 96 PowerSoil® Pro QIAcube® HT Kit excelled across all performance parameters. We further used the nanoliter dispensing system I.DOT One to miniaturize Illumina amplicon and metagenomic library preparation volumes by a factor of 5 and 10, respectively, with no significant impact on the observed microbial communities. With these protocols, DNA extraction, metagenomic, or amplicon library preparation for one 96-well plate are approx. 3, 5, and 6 hours, respectively. Furthermore, the miniaturization of amplicon and metagenome library preparation reduces the chemical and plastic costs from 5.0 to 3.6 and 59 to 7.3 USD pr. sample. This enhanced efficiency and cost-effectiveness will enable researchers to undertake studies with greater sample sizes and diversity, thereby providing a richer, more detailed view of microbial communities and their dynamics.

The clinical value of mNGS of bronchoalveolar lavage fluid versus traditional microbiological tests for pathogen identification and prognosis of severe pneumonia (NT-BALF):study protocol for a prospective multi-center randomized clinical trial.

BACKGROUND: Early, rapid, and accurate pathogen diagnosis can help clinicians select targeted treatment options, thus improving prognosis and reducing mortality rates of severe pneumonia. Metagenomic next-generation sequencing (mNGS) has a higher sensitivity and broader pathogen spectrum than traditional microbiological tests. However, the effects of mNGS-based antimicrobial treatment procedures on clinical outcomes and cost-effectiveness in patients with severe pneumonia have not been evaluated. METHODS: This is a regional, multi-center, open, prospective, randomized controlled trial to evaluate that whether the combination of mNGS and traditional testing methods could decrease 28-day call-cause mortality with moderate cost-effectiveness. A total of 192 patients with severe pneumonia will be recruited from four large tertiary hospitals in China. Bronchoalveolar lavage fluid will be obtained in all patients and randomly assigned to the study group (mNGS combined with traditional microbiological tests) or the control group (traditional microbiological tests only) in a 1:1 ratio. Individualized antimicrobial treatment and strategy will be selected according to the analysis results. The primary outcome is 28-day all-cause mortality. The secondary outcomes are ICU and hospital length of stay (LOS), ventilator-free days and ICU-free days, consistency between mNGS and traditional microbiological tests, detective rate of mNGS and traditional microbiological tests, turn-out time, time from group allocation to start of treatment, duration of vasopressor support, types and duration of anti-infective regimens, source of drug-resistant bacteria or fungi, and ICU cost. DISCUSSION: The clinical benefits of mNGS are potentially significant, but its limitations should also be considered. TRIAL REGISTRATION: ChineseClinicalTrialRegistry.org, ChiCTR2300076853. Registered on 22 October 2023.

Comprehensive assessment of 11 de novo HiFi assemblers on complex eukaryotic genomes and metagenomes.

Pacific Biosciences (PacBio) HiFi sequencing technology generates long reads (>10 kbp) with very high accuracy (<0.01% sequencing error). Although several de novo assembly tools are available for HiFi reads, there are no comprehensive studies on the evaluation of these assemblers. We evaluated the performance of 11 de novo HiFi assemblers on (1) real data for three eukaryotic genomes; (2) 34 synthetic data sets with different ploidy, sequencing coverage levels, heterozygosity rates, and sequencing error rates; (3) one real metagenomic data set; and (4) five synthetic metagenomic data sets with different composition abundance and heterozygosity rates. The 11 assemblers were evaluated using quality assessment tool (QUAST) and benchmarking universal single-copy ortholog (BUSCO). We also used several additional criteria, namely, completion rate, single-copy completion rate, duplicated completion rate, average proportion of largest category, average distance difference, quality value, run-time, and memory utilization. Results show that hifiasm and hifiasm-meta should be the first choice for assembling eukaryotic genomes and metagenomes with HiFi data. We performed a comprehensive benchmarking study of commonly used assemblers on complex eukaryotic genomes and metagenomes. Our study will help the research community to choose the most appropriate assembler for their data and identify possible improvements in assembly algorithms.

Modelling the effectiveness of surveillance based on metagenomics in detecting, monitoring, and forecasting antimicrobial resistance in livestock production under economic constraints.

Current surveillance of antimicrobial resistance (AMR) is mostly based on testing indicator bacteria using minimum inhibitory concentration (MIC) panels. Metagenomics has the potential to identify all known antimicrobial resistant genes (ARGs) in complex samples and thereby detect changes in the occurrence earlier. Here, we simulate the results of an AMR surveillance program based on metagenomics in the Danish pig population. We modelled both an increase in the occurrence of ARGs and an introduction of a new ARG in a few farms and the subsequent spread to the entire population. To make the simulation realistic, the total cost of the surveillance was constrained, and the sampling schedule was set at one pool per month with 5, 20, 50, or 100 samples. Our simulations demonstrate that a pool of 20-50 samples and a sequencing depth of 250 million fragments resulted in the shortest time to detection in both scenarios, with a time delay to detection of change of [Formula: see text]15 months in all scenarios. Compared with culture-based surveillance, our simulation indicates that there are neither significant reductions nor increases in time to detect a change using metagenomics. The benefit of metagenomics is that it is possible to monitor all known resistance in one sampling and laboratory procedure in contrast to the current monitoring that is based on the phenotypic characterisation of selected indicator bacterial species. Therefore, overall changes in AMR in a population will be detected earlier using metagenomics due to the fact that the resistance gene does not have to be transferred to and expressed by an indicator bacteria before it is possible to detect.

Cross-cohort single-nucleotide-variant profiling of gut microbiota suggests a novel gut-health assessment approach.

IMPORTANCE: Most studies focused much on the change in abundance and often failed to explain the microbiome variation related to disease conditions, Herein, we argue that microbial genetic changes can precede the ecological changes associated with the host physiological changes and, thus, would offer a new information layer from metagenomic data for predictive modeling of diseases. Interestingly, we preliminarily found a few genetic biomarkers on SCFA production can cover most chronic diseases involved in the meta-analysis. In the future, it is of both scientific and clinical significance to further explore the dynamic interactions between adaptive evolution and ecology of gut microbiota associated with host health status.

Microecological health assessment of water environment and sediment based on metagenomics: a case study of Guixi River in Chongqing, China.

River sediment is vital in containing water pollution and strengthening water remediation. This paper has conducted a study on the microecological health assessment of the sediment and water body of Guixi River in Dianjiang, Chongqing, China, using metagenomics sequencing and microbial biological integrity index (M-IBI) technology. The analysis of physical and chemical characteristics shows that the concentration of TN varies from 2.62 to 9.76 mg/L in each sampling section, and the eutrophication of the water body is relatively severe. The proportion of Cyanobacteria in the sampling section at the sink entrance is higher than that of other sites, where there are outbreaks of water blooms and potential hazards to human health. The dominant functions of each site include carbon metabolism, TCA cycle, and pyruvate metabolism. In addition, the main virulence factors and antibiotic resistance genes in sediment are Type IV pili (VF0082), LOS (CVF494), MymA operon (CVF649), and macrolide resistance genes macB, tetracyclic tetA (58), and novA. Correlation analysis of environmental factors and microorganisms was also performed, and it was discovered that Thiothrix and Acidovorax had obvious gene expression in the nitrogen metabolism pathway, and the Guixi River Basin had a self-purification capacity. Finally, based on the microecological composition of sediment and physical and chemical characteristics of the water body, the health assessment was carried out, indicating that the main pollution area was Dianjiang Middle School and the watershed near the sewage treatment plant. The findings should theoretically support an in-depth assessment of the water environment's microecological health.

Assessment of metagenomic workflows using a newly constructed human gut microbiome mock community.

To quantify the biases introduced during human gut microbiome studies, analyzing an artificial mock community as the reference microbiome is indispensable. However, there are still limited resources for a mock community which well represents the human gut microbiome. Here, we constructed a novel mock community comprising the type strains of 18 major bacterial species in the human gut and assessed the influence of experimental and bioinformatics procedures on the 16S rRNA gene and shotgun metagenomic sequencing. We found that DNA extraction methods greatly affected the DNA yields and taxonomic composition of sequenced reads, and that some of the commonly used primers for 16S rRNA genes were prone to underestimate the abundance of some gut commensal taxa such as Erysipelotrichia, Verrucomicrobiota and Methanobacteriota. Binning of the assembled contigs of shotgun metagenomic sequences by MetaBAT2 produced phylogenetically consistent, less-contaminated bins with varied completeness. The ensemble approach of multiple binning tools by MetaWRAP can improve completeness but sometimes increases the contamination rate. Our benchmark study provides an important foundation for the interpretation of human gut microbiome data by providing means for standardization among gut microbiome data obtained with different methodologies and will facilitate further development of analytical methods.

Population Genomic Screening for Three Common Hereditary Conditions : A Cost-Effectiveness Analysis.

BACKGROUND: The cost-effectiveness of screening the U.S. population for Centers for Disease Control and Prevention (CDC) Tier 1 genomic conditions is unknown. OBJECTIVE: To estimate the cost-effectiveness of simultaneous genomic screening for Lynch syndrome (LS), hereditary breast and ovarian cancer syndrome (HBOC), and familial hypercholesterolemia (FH). DESIGN: Decision analytic Markov model. DATA SOURCES: Published literature. TARGET POPULATION: Separate age-based cohorts (ages 20 to 60 years at time of screening) of racially and ethnically representative U.S. adults. TIME HORIZON: Lifetime. PERSPECTIVE: U.S. health care payer. INTERVENTION: Population genomic screening using clinical sequencing with a restricted panel of high-evidence genes, cascade testing of first-degree relatives, and recommended preventive interventions for identified probands. OUTCOME MEASURES: Incident breast, ovarian, and colorectal cancer cases; incident cardiovascular events; quality-adjusted survival; and costs. RESULTS OF BASE-CASE ANALYSIS: Screening 100 000 unselected 30-year-olds resulted in 101 (95% uncertainty interval [UI], 77 to 127) fewer overall cancer cases and 15 (95% UI, 4 to 28) fewer cardiovascular events and an increase of 495 quality-adjusted life-years (QALYs) (95% UI, 401 to 757) at an incremental cost of $33.9 million (95% UI, $27.0 million to $41.1 million). The incremental cost-effectiveness ratio was $68 600 per QALY gained (95% UI, $41 800 to $88 900). RESULTS OF SENSITIVITY ANALYSIS: Screening 30-, 40-, and 50-year-old cohorts was cost-effective in 99%, 88%, and 19% of probabilistic simulations, respectively, at a $100 000-per-QALY threshold. The test costs at which screening 30-, 40-, and 50-year-olds reached the $100 000-per-QALY threshold were $413, $290, and $166, respectively. Variant prevalence and adherence to preventive interventions were also highly influential parameters. LIMITATIONS: Population averages for model inputs, which were derived predominantly from European populations, vary across ancestries and health care environments. CONCLUSION: Population genomic screening with a restricted panel of high-evidence genes associated with 3 CDC Tier 1 conditions is likely to be cost-effective in U.S. adults younger than 40 years if the testing cost is relatively low and probands have access to preventive interventions. PRIMARY FUNDING SOURCE: National Human Genome Research Institute.

Metagenomics Provides a Deeper Assessment of the Diversity of Bacterial Communities in Polar Soils Than Metabarcoding.

The diversity of soil bacteria was analyzed via metabarcoding and metagenomic approaches using DNA samples isolated from the biocrusts of 12 different Arctic and Antarctic sites. For the metabarcoding approach, the V3-4 region of the 16S rRNA was targeted. Our results showed that nearly all operational taxonomic units (OTUs = taxa) found in metabarcoding analyses were recovered in metagenomic analyses. In contrast, metagenomics identified a large number of additional OTUs absent in metabarcoding analyses. In addition, we found huge differences in the abundance of OTUs between the two methods. The reasons for these differences seem to be (1) the higher sequencing depth in metagenomics studies, which allows the detection of low-abundance community members in metagenomics, and (2) bias of primer pairs used to amplify the targeted sequence in metabarcoding, which can change the community composition dramatically even at the lower taxonomic levels. We strongly recommend using only metagenomic approaches when establishing the taxonomic profiles of whole biological communities.

A low-cost, high-throughput microfluidic nano-culture platform for functional metagenomics.

Functional metagenomics is an attractive culture-independent approach for functional screening of diverse microbiomes to identify known and novel genes. Since functional screening can involve sifting through tens of thousands of metagenomic library clones, an easy high-throughput screening approach is desirable. Here, we demonstrate a proof-of-concept application of a low-cost, high-throughput droplet based microfluidic assay to the selection of antibiotic resistance genes from a soil metagenomic library. Metagenomic library members encapsulated in nanoliter volume water-in-oil droplets were printed on glass slides robotically, and cell growth in individual drops in the presence of ampicillin was imaged and quantified to identify ampicillin-resistant clones. From the hits, true positives were confirmed by sequencing and functional validation. The ease of liquid handling, ease of set-up, low cost, and robust workflow makes the droplet-based nano-culture platform a promising candidate for screening and selection assays for functional metagenomic libraries.

A case for investment in clinical metagenomics in low-income and middle-income countries.

Clinical metagenomics is the diagnostic approach with the broadest capacity to detect both known and novel pathogens. Clinical metagenomics is costly to run and requires infrastructure, but the use of next-generation sequencing for SARS-CoV-2 molecular epidemiology in low-income and middle-income countries (LMICs) offers an opportunity to direct this infrastructure to the establishment of clinical metagenomics programmes. Local implementation of clinical metagenomics is important to create relevant systems and evaluate cost-effective methodologies for its use, as well as to ensure that reference databases and result interpretation tools are appropriate to local epidemiology. Rational implementation, based on the needs of LMICs and the available resources, could ultimately improve individual patient care in instances in which available diagnostics are inadequate and supplement emerging infectious disease surveillance systems to ensure the next pandemic pathogen is quickly identified.

Microbiota and environmental health monitoring of mouse colonies by metagenomic shotgun sequencing.

Metagenomic next-generation sequencing (mNGS) allows the monitoring of microbiota composition of murine colonies employed for scientific purposes in a single test by assessing the composition of gut microbiome and the detection of pathogens from fecal pellets. In this study, we tested the potential use of mNGS for monitoring both microbiota composition and the presence of pathogens through Environmental Health Monitoring, by using exhaust dust collection filters derived from individually ventilated cages (IVC) systems.mNGS analysis was performed on nucleic acids isolated from filters collecting air from the exhaust of: (1) cages with mice housed in a non-pathogen free facility; (2) animal-free cages with clean chow and bedding from the same facility; (3) cages housing mice from a specific-pathogen free (SPF) facility. mNGS results revealed correspondence between microbiome composition from fecal pellets and filter, including pathogenic bacteria (Helicobacter hepaticus, Helicobacter typhlonius, Chlamydia muridarum, Rodentibacter pneumotropicus, Citrobacter rodentium), intestinal protozoa (Tritrichomonas muris, Spironucleus muris) nematoda (Aspiculuris tetraptera) and eukaryotic parasites (Myocoptes musculinus), present in the colony. Entamoeba muris and Syphacia obvelata were detected in fecal pellets but not in filter. The animal free exhaust dust filter, exposed to clean cages (no mice) placed in the IVC after removal of all mice, exhibited the presence of the same pathogens due to contaminated connecting pipes, confirming the sensitivity of the approach. Conversely, the filter from SPF colony revealed the absence of pathogens.The current use of exhaust dust collection filters in health surveillance requires multiple molecular tests to identify specific pathogens and does not provide information on the colony microbiome. This work provides the proof-of-principle that assaying exhaust dust collection filters by mNGS for microbiota monitoring of laboratory mice is feasible. In its daily application, results suggest the usefulness of the test in SPF facilities, where pathogenic micro-organisms are expected to be absent. mNGS analysis of exhaust dust collection filters allows the analysis of multiple cages, reducing the number of tests required for pathogen detection and corresponding costs, and avoiding the use of sentinel mice.

Assessment of Rapid MinION Nanopore DNA Virus Meta-Genomics Using Calves Experimentally Infected with Bovine Herpes Virus-1.

Bovine respiratory disease (BRD), which is the leading cause of morbidity and mortality in cattle, is caused by numerous known and unknown viruses and is responsible for the widespread use of broad-spectrum antibiotics despite the use of polymicrobial BRD vaccines. Viral metagenomics sequencing on the portable, inexpensive Oxford Nanopore Technologies MinION sequencer and sequence analysis with its associated user-friendly point-and-click Epi2ME cloud-based pathogen identification software has the potential for point-of-care/same-day/sample-to-result metagenomic sequence diagnostics of known and unknown BRD pathogens to inform a rapid response and vaccine design. We assessed this potential using in vitro viral cell cultures and nasal swabs taken from calves that were experimentally challenged with a single known BRD-associated DNA virus, namely, bovine herpes virus 1. Extensive optimisation of the standard Oxford Nanopore library preparation protocols, particularly a reduction in the PCR bias of library amplification, was required before BoHV-1 could be identified as the main virus in the in vitro cell cultures and nasal swab samples within approximately 7 h from sample to result. In addition, we observed incorrect assignment of the bovine sequence to bacterial and viral taxa due to the presence of poor-quality bacterial and viral genome assemblies in the RefSeq database used by the EpiME Fastq WIMP pathogen identification software.

Critical assessment of pan-genomic analysis of metagenome-assembled genomes.

Pan-genome analyses of metagenome-assembled genomes (MAGs) may suffer from the known issues with MAGs: fragmentation, incompleteness and contamination. Here, we conducted a critical assessment of pan-genomics of MAGs, by comparing pan-genome analysis results of complete bacterial genomes and simulated MAGs. We found that incompleteness led to significant core gene (CG) loss. The CG loss remained when using different pan-genome analysis tools (Roary, BPGA, Anvi'o) and when using a mixture of MAGs and complete genomes. Contamination had little effect on core genome size (except for Roary due to in its gene clustering issue) but had major influence on accessory genomes. Importantly, the CG loss was partially alleviated by lowering the CG threshold and using gene prediction algorithms that consider fragmented genes, but to a less degree when incompleteness was higher than 5%. The CG loss also led to incorrect pan-genome functional predictions and inaccurate phylogenetic trees. Our main findings were supported by a study of real MAG-isolate genome data. We conclude that lowering CG threshold and predicting genes in metagenome mode (as Anvi'o does with Prodigal) are necessary in pan-genome analysis of MAGs. Development of new pan-genome analysis tools specifically for MAGs are needed in future studies.